Investigating the Mini-Challenge 2 of VAST Challenge 2021
Given the data sources provided, identify potential informal or unofficial relationships among GASTech personnel. Provide evidence for these relationships. Please limit your response to 8 images and 500 words.
Both were frequenting the following places together at similar times and for similar durations: - Chostus Hotel
- Frydos Autosupply n’ More
- Gathering at Engineer’s Lars Home on 10th Jan Late Evening
- Hippokampos on 15th Jan Afternoon
- Ouzeri Elian on 6th Jan Afternoon
tmap_mode("view")
Q5.4.1 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==7)) + # Extract Elsa's path
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==33)) + # Extract Brand's path
tm_lines(col = "blue",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf) +
tm_dots(col = "Location.Type",
id = "Location", # Bold in group
popup.vars = "Location Type:" =="Location.Type",
size = 0.2)
Q5.4.1
Hennie seem to stay in two separate homes on different evenings:
- Either with Lidelse and Birgitta
- Or with Inga, Loreto and Isia
tmap_mode("view")
Q5.4.2 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==21)) + # Extract Hennie's path
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf %>%
filter(Location == "Shared Home B - 14 Lidelse 18 Birgitta 21 Hennie" | Location == "Shared Home E - 13 Inga 15 Loreto 16 Isia 21 Hennie")) +
tm_dots(col = "green",
size = 0.2)
Q5.4.2
Although both are staying in the same housing together with Kanon, both seem to frequent the same coffee chain in the mornings and food outlet in the evenings together. Kanon was not present during these meal times.
- Coffee Cameleon
- Katerina’s Cafe
tmap_mode("view")
Q5.4.3 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==29 & day !=19)) + # Extract Bertrand's path and removed 19th Jan since its single point throws an error in the linestring
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==6)) + # Extract Linnea's path
tm_lines(col = "blue",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf) +
tm_dots(col = "Location.Type",
id = "Location", # Bold in group
popup.vars = "Location Type:" =="Location.Type",
size = 0.2)
Q5.4.3
Similarly, although both are staying in the same housing together with Hennie, both seem to frequent the same coffee chains in the mornings and food outlets in the afternoon and evenings together. Hennie was not present during these meal times.
- Guy’s Gyros
- Bean There Done That
- Katerina’s Cafe
- Hallowed Grounds
tmap_mode("view")
Q5.4.4 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==14)) + # Extract Lidelse's path
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==18)) + # Extract Birgitta's path
tm_lines(col = "blue",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf) +
tm_dots(col = "Location.Type",
id = "Location", # Bold in group
popup.vars = "Location Type:" =="Location.Type",
size = 0.2)
Q5.4.4
Do you see evidence of suspicious activity? Identify 1- 10 locations where you believe the suspicious activity is occurring, and why. Please limit your response to 10 images and 500 words.
Suspicious Activities Can Be In The Following Forms:
1) Unknown locations not found on map
2) Gathering of two or more individuals at the same location at the same hour for extended periods
3) Individuals frequenting unusual places at abnormal hours
These are locations where there were multiple instances of GPS points remaining stationary for more than 10 mins. These unknown locations do not conform to known locations on the furnished map pic.
tmap_mode("view")
Q5.5.1 <- tm_shape(mc2) +
tm_rgb(mc2, r = 1,g = 2,b = 3,
alpha = NA,
saturation = 1,
interpolate = TRUE,
max.value = 255) +
tm_shape(spots_median_sf %>%
filter(Location.Type != "Unknown")) +
tm_dots(col = "Location.Type",
id = "Location", # Bold in group
popup.vars = "Location Type:" =="Location.Type",
size = 0.2) +
tm_shape(spots_median_sf %>%
filter(Location.Type == "Unknown")) +
tm_dots(col = "black",
id = "Location", # Bold in group
popup.vars = "Location Type:" =="Location.Type",
size = 0.2)
Q5.5.1
Showcasing only residential points, Bodrogi (ID: 15, black line), Vann (ID: 16, blue line), Osvaldo (ID:21, purple line) and Mies (ID:24, red line) were seen patroling key executives’ houses located near the centre area. (Hover over the lines and points to see the ID and owner of each residence)
tmap_mode("view")
Q5.5.2 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==15)) + # Extract Bodrogi's path
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==16)) + # Extract Vann's path
tm_lines(col = "blue",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==21)) + # Extract Osvaldo's path
tm_lines(col = "purple",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==24)) + # Extract Mies's path
tm_lines(col = "red",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf %>%
filter(Location.Type == "Residential")) +
tm_dots(col = "green",
size = 0.2)
Q5.5.2
It begs the question as to the main cause of Isande’s wayward driving. Though it’s highly unlikely that he veers from side to side throughout his drive, it suggests that his GPS device is either faulty or that it has been tampered to cover his tracks. Relooking at the places he visited, there is little to suggest that he might be a risky character. But nonetheless, his wayward movements remain suspicious.
tmap_mode("view")
Q5.5.3 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==28)) + # Extract Isande's path
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf) +
tm_dots(col = "Location.Type",
id = "Location", # Bold in group
popup.vars = "Location Type:" =="Location.Type",
size = 0.2)
Q5.5.3
On 18th Jan, Bodrogi (ID: 15, black line) met Nubarron (ID: 22, blue line) at Kronos Capital in the afternoon. This location was visited in the morning by Nubarron, as well as Vann (ID: 34, red line) in the evening. Herrero (ID:25, green line) was also stationary for approx. 24 hours in this location on 19th Jan.
tmap_mode("view")
Q5.5.4 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==15 & day==18)) + # Extract Bodrogi's path on 18th Jan
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==22 & day==18)) + # Extract Nubarron's path on 18th Jan
tm_lines(col = "blue",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==34 & day==18)) + # Extract Vann's path on 18th Jan
tm_lines(col = "red",
lty = 1,
id = "RoleNName") +
tm_shape(gps_path %>% filter(id==25 & day==19)) + # Extract Herrero's path on 19th Jan
tm_lines(col = "green",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf %>%
filter(Location == "Kronos Capital")) +
tm_dots(col = "green",
size = 0.2)
Q5.5.4
A large gathering of 13 individuals, from both the IT and Geological department, was spotted in the late evening on 10th Jan.
tmap_mode("view")
Q5.5.5 <- tm_shape(sea_poly) +
tm_polygons(col="lightblue") +
tm_shape(Kronos_sf_small) +
tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
tm_polygons(col = "white") +
# Extract a multitude of visitors to Lars' Home on Jan 10th Late Evening
tm_shape(gps_path %>%
filter(day==10 & id==1 |
id==2 |
id==5 |
id==6 |
id==7 |
id==8 |
id==9 |
id==11 |
id==14 |
id==18 |
id==19 |
id==25 |
id==33)) +
tm_lines(col = "black",
lty = 1,
id = "RoleNName") +
tm_shape(spots_median_sf %>%
filter(Location == "2 Engineer Lars's Home")) +
tm_dots(col = "green",
size = 0.2)
Q5.5.5
If you solved this mini-challenge in 2014, how did you approach it differently this year?
We did not attempt this mini-challenge in 2014.
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